Paper Number
2228
Paper Type
Complete Research Paper
Abstract
The use of artificial intelligence (AI) revolutionises both everyday life and business processes. In e-commerce, AI enables companies to exploit new potentials based on predictions in various deployment scenarios. In dynamic pricing, AI-driven prediction models are used to determine the optimal price and thus enhance sales. Yet, these algorithms vary in terms of nature, complexity, and application area. Hence, it remains open as to which algorithm fits this specific use case and how to integrate these into the pricing processes and strategies. Furthermore, the extant literature lacks a systematized, holistic overview of existing approaches and algorithms. Addressing this gap, our structured literature review provides a comprehensive overview of current approaches and implemented algorithms in dynamic pricing. We categorize the literature into four clusters: activity level, application procedure, data foundation, and algorithms, offering valuable insights into the current state of research in this domain.
Recommended Citation
Tomitza, Christoph; Ibrahimli, Ulvi; and Herm, Lukas-Valentin, "AI-Based Methods of Dynamic Pricing in E-Commerce: A Systematization of Literature" (2024). ECIS 2024 Proceedings. 6.
https://aisel.aisnet.org/ecis2024/track03_ai/track03_ai/6
AI-Based Methods of Dynamic Pricing in E-Commerce: A Systematization of Literature
The use of artificial intelligence (AI) revolutionises both everyday life and business processes. In e-commerce, AI enables companies to exploit new potentials based on predictions in various deployment scenarios. In dynamic pricing, AI-driven prediction models are used to determine the optimal price and thus enhance sales. Yet, these algorithms vary in terms of nature, complexity, and application area. Hence, it remains open as to which algorithm fits this specific use case and how to integrate these into the pricing processes and strategies. Furthermore, the extant literature lacks a systematized, holistic overview of existing approaches and algorithms. Addressing this gap, our structured literature review provides a comprehensive overview of current approaches and implemented algorithms in dynamic pricing. We categorize the literature into four clusters: activity level, application procedure, data foundation, and algorithms, offering valuable insights into the current state of research in this domain.
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